B-Raf Associates with and Activates the NHE1 Isoform of the Na+/H+ Exchanger
Bibliographic record
Abstract
The serine/threonine kinase B-Raf is the second most frequently occurring human oncogene after Ras. Mutations of B-Raf occur with the highest incidences in melanoma, and the most common mutant, V600E, renders B-Raf constitutively active. The sodium proton exchanger isoform 1 (NHE1) is a ubiquitously expressed plasma membrane protein responsible for regulating intracellular pH, cell volume, cell migration, and proliferation. A screen of protein kinases that bind to NHE1 revealed that B-Raf bound to the cytosolic regulatory tail of NHE1. Immunoprecipitation of NHE1 from HeLa and HEK cells confirmed the association of B-Raf with NHE1 in vivo. The expressed and purified C-terminal 182 amino acids of the NHE1 protein were also shown to associate with B-Raf protein in vitro. Because treatment with the kinase inhibitor sorafenib decreased NHE1 activity in HeLa and HEK cells, we examined the role of B-Raf in regulating NHE1 in malignant melanoma cells. Melanoma cells with the B-Raf(V600E) mutation demonstrated increased resting intracellular pH that was dependent on elevated NHE1 activity. NHE1 activity after an acute acid load was also elevated in these cell lines. Moreover, inhibition of B-Raf activity by either sorafenib, PLX4720, or siRNA reduction of B-Raf levels abolished ERK phosphorylation and decreased NHE1 activity. These results demonstrate that B-Raf associates with and stimulates NHE1 activity and that B-Raf(V600E) also increases NHE1 activity that raises intracellular pH.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".